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We present an adaptation of the MA-LBR scheme to the Monge-Amp{\`e}re equation with second boundary value condition, provided the target is a convex set. This yields a fast adaptive method to numerically solve the Optimal Transport problem…

Numerical Analysis · Mathematics 2018-07-19 Jean-David Benamou , Vincent Duval

We present a new approach to Bayesian inference that entirely avoids Markov chain simulation, by constructing a map that pushes forward the prior measure to the posterior measure. Existence and uniqueness of a suitable measure-preserving…

Computation · Statistics 2012-08-31 Tarek A. El Moselhy , Youssef M. Marzouk

We study the problem of identifying an optimal coupling between input-output distributional data generated by a causal dynamical system. The coupling is required to satisfy prescribed marginal distributions and a causality constraint…

Systems and Control · Electrical Eng. & Systems 2026-04-03 Daran Xu , Amirhossein Taghvaei

Change of numeraire is a classical tool in mathematical finance. Campi-Laachir-Martini established its applicability to martingale optimal transport. We note that the results of Campi-Laachir-Martini extend to the case of weak martingale…

Probability · Mathematics 2024-06-12 Mathias Beiglböck , Gudmund Pammer , Lorenz Riess

We establish a connection between Optimal Transport Theory and classical Convection Theory for geophysical flows. Our starting point is the model designed few years ago by Angenent, Haker and Tannenbaum to solve some Optimal Transport…

Analysis of PDEs · Mathematics 2015-05-13 Yann Brenier

We show that introducing an exponential cut-off on a suitable Sobolev norm facilitates the proof of quasi-invariance of Gaussian measures with respect to Hamiltonian PDE flows and allows us to establish the exact Jacobi formula for the…

Analysis of PDEs · Mathematics 2022-07-04 Giuseppe Genovese , Renato Lucà , Nikolay Tzvetkov

We propose a practical Bayesian optimization method using Gaussian process regression, of which the marginal likelihood is maximized where the number of model selection steps is guided by a pre-defined threshold. Since Bayesian optimization…

Machine Learning · Statistics 2020-10-19 Jungtaek Kim , Seungjin Choi

Many causal parameters depend on a moment of the joint distribution of potential outcomes. Such parameters are especially relevant in policy evaluation settings, where noncompliance is common and accommodated through the model of Imbens &…

Econometrics · Economics 2023-11-17 Daniel Ober-Reynolds

We study martingale inequalities from an analytic point of view and show that a general martingale inequality can be reduced to a pair of deterministic inequalities in a small number of variables. More precisely, the optimal bound in the…

Probability · Mathematics 2014-10-21 Mathias Beiglböck , Marcel Nutz

Let $(Z_t)_{t\geq 0}$ denote the derivative martingale of branching Brownian motion, i.e.\@ the derivative with respect to the inverse temperature of the normalized partition function at critical temperature. A well-known result by Lalley…

Probability · Mathematics 2018-06-20 Pascal Maillard , Michel Pain

We consider the problem of maximising expected utility from terminal wealth in a semimartingale setting, where the semimartingale is written as a sum of a time-changed Brownian motion and a finite variation process. To solve this problem,…

Probability · Mathematics 2024-07-04 Giulia Di Nunno , Hannes Haferkorn , Asma Khedher , Michèle Vanmaele

We consider inverse problems in Hilbert spaces under correlated Gaussian noise and use a Bayesian approach to find their regularised solution. We focus on mildly ill-posed inverse problems with the noise being generalised derivative of…

Statistics Theory · Mathematics 2023-11-21 Natalia Bochkina , Jenovah Rodrigues

We introduce and study a multi-marginal optimal partial transport problem. Under a natural and sharp condition on the dominating marginals, we establish uniqueness of the optimal plan. Our strategy of proof establishes and exploits a…

Analysis of PDEs · Mathematics 2015-08-10 Jun Kitagawa , Brendan Pass

In this note we prove that the local martingale part of a convex function f of a d-dimensional semimartingale X = M + A can be written in terms of an It^o stochastic integral \int H(X)dM, where H(x) is some particular measurable choice of…

Probability · Mathematics 2011-04-01 Nastasiya F Grinberg

We study Brownian motors driven by colored non Gaussian noises, both in the overdamped regime and in the case with inertia, and analyze how the departure of the noise distribution from Gaussian behavior can affect its behavior. We analyze…

Statistical Mechanics · Physics 2009-11-10 S. Bouzat , H. S. Wio

Stochastic convex optimization, where the objective is the expectation of a random convex function, is an important and widely used method with numerous applications in machine learning, statistics, operations research and other areas. We…

Machine Learning · Computer Science 2016-11-23 Vitaly Feldman , Cristobal Guzman , Santosh Vempala

We completely characterise the optimal solutions for the three-marginal optimal transport problem - introduced in [K. Bolbotowski, G. Bouchitt\'e, Kantorovich-Rubinstein duality theory for the Hessian, 2024, preprint], and whose relaxation…

Optimization and Control · Mathematics 2025-02-14 Krzysztof J. Ciosmak

We study the influence of additional intermediate marginal distributions on the value of the martingale optimal transport problem. From a financial point of view, this corresponds to taking into account call option prices not only, as…

Mathematical Finance · Quantitative Finance 2023-11-03 Julian Sester

This short paper announces the main results of \cite{SBB2026}, where the Schr\"odinger--Bass Bridge (SBB) problem is introduced and studied in full generality. Here we provide a direct PDE derivation of the SBB system in dimension one,…

This paper studies distributional model risk in marginal problems, where each marginal measure is assumed to lie in a Wasserstein ball centered at a fixed reference measure with a given radius. Theoretically, we establish several…

Optimization and Control · Mathematics 2023-07-04 Yanqin Fan , Hyeonseok Park , Gaoqian Xu